Close the gap between data analysts and data scientists with the dbt Cloud <> Databricks Spark integration. This integration enables data analysts to build, test, and deploy data transformations for structured and unstructured data sets within a single unified analytics platform.
Unify Teams & Tech: Maintaining separate data workflows multiplies infrastructure and divides teams. Databricks + dbt enables analysts to model complete datasets from the same platform trusted by their data science counterparts.
Go Big: Machine Learning and AI datasets can be extremely large, making them difficult to clean and query in a consistent manner. By combining Databricks and dbt Cloud, organizations can apply analytic best practices like version control, testing, scheduling, and documentation without sacrificing speed or reliability.
Stay Flexible: dbt and Spark are both open source projects with a number of unique contributors. By putting open source solutions at the heart of your ecosystem you benefit from continuous innovation, community support, and a much higher degree of flexibility than closed-source alternatives.
Principal Code Connoisseur, GoDataDriven